Marshmallow

About Marshmallow

We started Marshmallow when we found out how unfair insurance prices are for people who move to the UK. All because the industry hasn’t given this huge cohort of people a second’s thought, and isn’t set up to price them properly. 

We saw an opportunity to do things differently, so we made it our mission to back the ones who step outside the norm. Since we started, we’ve helped 100,000s of people get a fairer deal on their car insurance. Using technology, we serve people that are often overlooked by financial services companies, solving important problems for people who need it most. 

We know there are millions of marginalised customers out there. And we know that they face unique problems that most companies aren’t even aware of. We believe that our future is helping these people by learning about their experiences, and building our company around their needs. And there are strong signs that there’s a need for a company like us. Earlier this year we hit profitability, which is a huge milestone, but the most exciting thing is that we’re only just getting started.

How we work

We’re really proud of the culture we’ve created. We push for progress every day, because we know that we’ll only hit big milestones by taking lots of smaller steps. We’re always open to helping our team mates, sharing our ideas, experience and knowledge to solve problems together. We take risks, think creatively and experiment relentlessly to meet our customer’s needs, and never pass blame when things go wrong. We encourage people at all levels to take ownership of their work, and to be bold in challenging how we do things. Everyone has a voice and the opportunity to make an impact. 

And autonomy and ownership are only possible with clear direction. That’s why we collaborate to do in-depth planning twice a year, and make sure we leave with clear goals and objectives that flow from top to bottom. To make sure we’re as aligned as possible across functions, most of our work rolls up into four tribes; Acquisition, Retention, Claims and Pricing, Underwriting & Fraud. Each tribe has multiple teams embedded in it, working cross-functionally to do great work.

We’re so excited for all of the challenges up ahead, and we need more people to help us tackle them! If life at Marshmallow sounds like it could be for you, explore our culture handbook or read our blog to find out more.

Machine Learning at Marshmallow

Our ML Eng team are critical to our ambition to continue to innovate and push the boundaries of how we assess risk, prevent fraud, offer customers unbeatable prices and how we as a business can maximise revenue and income. We’ve built an in-house platform, which we believe is one of a kind in insurance! The platform’s built with a bias for fast feedback loops, reliable and automated monitoring and training, self-service deployment by our analysts and data scientists using cost effective and performance optimised cloud workloads. This flexibility and speed is a massive competitive advantage for us and we want to continue to invest in this area, building a first-in-class platform and ultimately delivering a lot of value to the business.

What you’ll do:

• Able to estimate with accuracy and break down large tasks into smaller incremental deliverables that can be completed in a single sprint. 
• Frequently anticipates challenges in the software delivery process and when approaching the breaking down of large tasks.
• Puts significant effort into communicating requirements for platform goals and the criteria for success within those goals.
• They are outcome focused, recognize the machine learning platform needs, and how it relates to the business objectives.
• Able to lead cross team projects - able to approach another team, talk about dependencies and work out how to move forwards together.
• Contributes ideas for changes and new developments proactively, but pragmatically, with clear logical reasoning, based on evident needs, and justified with data where possible.
• Delivery
• Leads or can be the main contributor to medium to large sized projects (4-12 weeks).
• Demonstrates that they know how and when to effectively make trade offs in the face of ambiguity and uncertainty.
• Demonstrates a good balance for prioritising and addressing technical debt.
• Comfortable with changing priorities. They understand the rationale and the impact of proposed changes, and shift their plans accordingly.
• Ensures that they rarely become the bottleneck or a blocker. This means delegating andc/or collaborating effectively, and understanding when to disagree and commit.
• Pragmatic in terms of when it is safe to cut corners and why. They understand where it makes sense to push something out quickly without it being fully implemented, and then take responsibility for that decision.
• Effectively surfaces any changes to delivery that may affect Data Science or business objectives.
• Documents their work effectively for the understanding of current and future team members.
• Technical expertise
• Experience working on real-world machine learning problems and deploying solutions
• Has a high level of understanding of general machine learning platform architectures involving cloud infrastructure.
• Comfortable with our machine learning platform stack, how it integrates with the product platform and how end users interact with it. 
• Can work closely with Data Scientists/Machine Learning Engineers to build infrastructure to support and scale machine learning training, model deployment, and monitoring
• Able to quickly build a mental model of a new technology or approach, allowing them to assess pros and cons.
• Problem solving
• Can transparently work on large complex problems independently.
• Uses their experience to understand when to deviate from a well known path to try a new approach.
• Mentorship
• Actively invests time and skills into upskilling engineers at their level and below, and provide hands on support where needed.
• Trains data scientists on production processes and best practices
• Is helpful, collaborative and approachable for assistance in their domain of expertise / ownership.
• Devotes time and effort into documentation and onboarding processes.
• Communication
• Can communicate across multiple teams and collaborate effectively.
• Ensures that discussions impacting the machine learning platform and the machine learning engineering teams priorities are communicated across the team to avoid knowledge siloing.
• Surfaces blockers regularly, manages expectations around delivery when things may be held up, and ensures that any impacted stakeholders are aware.
• Raises ideas for changes and new developments proactively, but always in consultation with the wider Data Science team and considering our agreed priorities.
• Eng Org
• Drives visibility of the machine learning engineering discipline across Marshmallow.
• Proactively engages with stakeholders to identify opportunities and risks that they may not be aware of due to lack of understanding.
• Leverages their technical skills and knowledge of our culture to help us hire other machine learning engineers who will be a good fit. This could be interviewing, test reviewing, making improvements to our process or contributing to our employer brand.

Perks of the job

• Flexible working - Spend 3 days a week with your team in our new collaborative London office, and own your own working hours. The rest is up to you *If this arrangement doesn’t work, don’t let it hold you back. We’re always open to making reasonable adjustments if this is a barrier to you in any way. Let us know and we’ll talk about our options
• Competitive bonus scheme - designed to reward and recognise high performance ????
• Flexible benefits budget - £50 per month to spend on a Ben Mastercard meaning you get your own benefits budget to spend on things you want. Whether that’s subscriptions, night classes (puppy yoga, anyone?), the big shop or a forest of houseplants. Pretty much anything goes ????
• Mental wellbeing support – Access therapy and mental health sessions through Oliva ????
• Learning and development – Personal budgets for books and training courses to help you grow in your role. Plus 2 days a year - on us! - to further your skillset ????
• Private health care - Enjoy all the benefits Vitality has to offer, including reduced gym memberships and discounts on smartwatches ????
• Medical cash plan - To help you with the costs of dental, optical and physio (plus more!)
• Tech scheme - Get the latest tech for less ????

Plus all the rest; 33 days holiday (including bank holidays), pension, cycle to work scheme, monthly team socials and company-wide socials every month!

The Process

Perm Interview Process:

1. TA Screen with Luke , our TA Lead (45 mins)
2. Past experience and Culture with Paul, our Head of Data Science (60 mins)
3. Technical Interview with Mason, Senior ML engineer, and Marilia, Principal DataScientist (60 mins)

Everyone belongs at Marshmallow

At Marshmallow, we want to hire people from all walks of life with the passion and skills needed to help us achieve our company mission. To do that, we're committed to hiring without judgement, prejudice or bias.

We encourage everyone to apply for our open roles. Gender identity, race, ethnicity, sexual orientation, age or background does not affect how we process job applications.

We're working hard to build an inclusive culture that empowers our people to do their best work, have fun and feel that they belong.